Modelling of runway excursions using Bayesian belief networks

Project Portfolio Risk Response Selection Using Bayesian Belief Networks

Risk identification, impact assessment, and response planning constitute three building blocks of project risk management. Correspondingly, three types of interactions could be envisioned between risks, between impacts of several risks on a portfolio component, and between several responses. While the interdependency of risks is a well-recognized issue, the other two types of interactions remai...

Modelling ecosystem services using Bayesian belief networks: Burggravenstroom case study

While being studied by scientists for decades, the term ecosystem services was only recently introduced to the general public. This introduction intended broad-scale recognition of ecosystems and their value for human wellbeing. Both quantitative and qualitative research on ecosystem services became emerging topics in scientific research. Ecosystem service prediction models were developed varyi...

Bridge Condition Modelling and Prediction Using Dynamic Bayesian Belief Networks

Belief networks / Bayesian networks

Introduction In modeling real world tasks, one inevitably has to deal with uncertainty. This uncertainty is due to the fact that many facts are unknown and or simply ignored and summarized. Suppose that one morning you find out that your grass is wet. Is it due to rain, or is it due to the sprinkler? If there is no other information, you can only talk in terms of probabilities. In a probabilist...

Predicting Software Quality using Bayesian Belief Networks

In the absence of an agreed measure of software quality the density of defects has been a very commonly used surrogate measure. As a result there have been numerous attempts to build models for predicting the number of residual software defects. Typically, the key variables in these models are either size and complexity metrics or measures arising from testing information. There are, however, s...